• Record: found
  • Abstract: found
  • Article: found
Is Open Access

Distinct Allelic Patterns of Nanog Expression Impart Embryonic Stem Cell Population Heterogeneity

1 , 1 , 2 , 3 , 4 , *

PLoS Computational Biology

Public Library of Science

Read this article at

      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.


      Nanog is a principal pluripotency regulator exhibiting a disperse distribution within stem cell populations in vivo and in vitro. Increasing evidence points to a functional role of Nanog heterogeneity on stem cell fate decisions. Allelic control of Nanog gene expression was reported recently in mouse embryonic stem cells. To better understand how this mode of regulation influences the observed heterogeneity of NANOG in stem cell populations, we assembled a multiscale stochastic population balance equation framework. In addition to allelic control, gene expression noise and random partitioning at cell division were considered. As a result of allelic Nanog expression, the distribution of Nanog exhibited three distinct states but when combined with transcriptional noise the profile became bimodal. Regardless of their allelic expression pattern, initially uniform populations of stem cells gave rise to the same Nanog heterogeneity within ten cell cycles. Depletion of NANOG content in cells switching off both gene alleles was slower than the accumulation of intracellular NANOG after cells turned on at least one of their Nanog gene copies pointing to Nanog state-dependent dynamics. Allelic transcription of Nanog also raises issues regarding the use of stem cell lines with reporter genes knocked in a single allelic locus. Indeed, significant divergence was observed in the reporter and native protein profiles depending on the difference in their half-lives and insertion of the reporter gene in one or both alleles. In stem cell populations with restricted Nanog expression, allelic regulation facilitates the maintenance of fractions of self-renewing cells with sufficient Nanog content to prevent aberrant loss of pluripotency. Our findings underline the role of allelic control of Nanog expression as a prime determinant of stem cell population heterogeneity and warrant further investigation in the contexts of stem cell specification and cell reprogramming.

      Author Summary

      Nanog is a key factor influencing the decision of a stem cell to remain pluripotent or differentiate. Each embryonic stem cell (ESC) in a population exhibits fluctuating Nanog levels resulting in heterogeneity which affects cell fate specification. The allelic regulation of Nanog was demonstrated recently but its implications on population heterogeneity are unclear. We developed a multiscale population balance equation (PBE) model and compared our results with pertinent experimental studies. Under allelic control the profile of Nanog features three peaks or distinct states. Transcriptional noise causes the distribution to become bimodal as suggested previously. When stem cells carrying a reporter transgene in an allelically regulated locus were examined, we observed non-matching distributions of the endogenous and reporter proteins. This led us to investigate the performance of reporter systems depending on insertion of the transgene in one or both alleles and the protein degradation dynamics. Lastly, our model was employed to address how allelic regulation affects the maintenance of pluripotency in stem cells with a single Nanog allele deletion. A fraction of these cells remains pluripotent while deletion of a single allele does not simply reduce NANOG uniformly for all ESCs but modulates NANOG heterogeneity directly.

      Related collections

      Most cited references 39

      • Record: found
      • Abstract: found
      • Article: not found

      The ground state of embryonic stem cell self-renewal.

      In the three decades since pluripotent mouse embryonic stem (ES) cells were first described they have been derived and maintained by using various empirical combinations of feeder cells, conditioned media, cytokines, growth factors, hormones, fetal calf serum, and serum extracts. Consequently ES-cell self-renewal is generally considered to be dependent on multifactorial stimulation of dedicated transcriptional circuitries, pre-eminent among which is the activation of STAT3 by cytokines (ref. 8). Here we show, however, that extrinsic stimuli are dispensable for the derivation, propagation and pluripotency of ES cells. Self-renewal is enabled by the elimination of differentiation-inducing signalling from mitogen-activated protein kinase. Additional inhibition of glycogen synthase kinase 3 consolidates biosynthetic capacity and suppresses residual differentiation. Complete bypass of cytokine signalling is confirmed by isolating ES cells genetically devoid of STAT3. These findings reveal that ES cells have an innate programme for self-replication that does not require extrinsic instruction. This property may account for their latent tumorigenicity. The delineation of minimal requirements for self-renewal now provides a defined platform for the precise description and dissection of the pluripotent state.
        • Record: found
        • Abstract: found
        • Article: not found

        The homeoprotein Nanog is required for maintenance of pluripotency in mouse epiblast and ES cells.

        Embryonic stem (ES) cells derived from the inner cell mass (ICM) of blastocysts grow infinitely while maintaining pluripotency. Leukemia inhibitory factor (LIF) can maintain self-renewal of mouse ES cells through activation of Stat3. However, LIF/Stat3 is dispensable for maintenance of ICM and human ES cells, suggesting that the pathway is not fundamental for pluripotency. In search of a critical factor(s) that underlies pluripotency in both ICM and ES cells, we performed in silico differential display and identified several genes specifically expressed in mouse ES cells and preimplantation embryos. We found that one of them, encoding the homeoprotein Nanog, was capable of maintaining ES cell self-renewal independently of LIF/Stat3. nanog-deficient ICM failed to generate epiblast and only produced parietal endoderm-like cells. nanog-deficient ES cells lost pluripotency and differentiated into extraembryonic endoderm lineage. These data demonstrate that Nanog is a critical factor underlying pluripotency in both ICM and ES cells.
          • Record: found
          • Abstract: found
          • Article: not found

          Functional expression cloning of Nanog, a pluripotency sustaining factor in embryonic stem cells.

          Embryonic stem (ES) cells undergo extended proliferation while remaining poised for multilineage differentiation. A unique network of transcription factors may characterize self-renewal and simultaneously suppress differentiation. We applied expression cloning in mouse ES cells to isolate a self-renewal determinant. Nanog is a divergent homeodomain protein that directs propagation of undifferentiated ES cells. Nanog mRNA is present in pluripotent mouse and human cell lines, and absent from differentiated cells. In preimplantation embryos, Nanog is restricted to founder cells from which ES cells can be derived. Endogenous Nanog acts in parallel with cytokine stimulation of Stat3 to drive ES cell self-renewal. Elevated Nanog expression from transgene constructs is sufficient for clonal expansion of ES cells, bypassing Stat3 and maintaining Oct4 levels. Cytokine dependence, multilineage differentiation, and embryo colonization capacity are fully restored upon transgene excision. These findings establish a central role for Nanog in the transcription factor hierarchy that defines ES cell identity.

            Author and article information

            [1 ]Department of Chemical and Biological Engineering, State University of New York at Buffalo, Buffalo, New York, United States of America
            [2 ]Department of Biomedical Engineering, State University of New York at Buffalo, Buffalo, New York, United States of America
            [3 ]New York State Center of Excellence in Bioinformatics and Life Sciences, Buffalo, New York, United States of America
            [4 ]Western New York Stem Cell Culture and Analysis Center, State University of New York at Buffalo, Buffalo, New York, United States of America
            Northeastern University, United States of America
            Author notes

            The authors have declared that no competing interests exist.

            Conceived and designed the experiments: JW EST. Performed the experiments: JW EST. Analyzed the data: JW EST. Contributed reagents/materials/analysis tools: JW EST. Wrote the paper: JW EST.

            Role: Editor
            PLoS Comput Biol
            PLoS Comput. Biol
            PLoS Computational Biology
            Public Library of Science (San Francisco, USA )
            July 2013
            July 2013
            11 July 2013
            : 9
            : 7

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Pages: 13
            Funding support has been provided by the National Institutes of Health (NHLBI, R01HL103709) and the New York Stem Cell Science Trust (NYSTEM, contract C024355) to EST. This work was performed in part at the University at Buffalo's Center for Computational Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
            Research Article
            Computational Biology
            Developmental Biology
            Stem Cells
            Embryonic Stem Cells
            Stem Cell Lines
            Cell Differentiation
            Cell Fate Determination
            Biological Systems Engineering
            Mathematical Computing
            Probability Theory
            Markov Model
            Stochastic Processes

            Quantitative & Systems biology


            Comment on this article